%0 Conference Proceedings
%4 sid.inpe.br/marte2/2017/10.27.16.33.47
%2 sid.inpe.br/marte2/2017/10.27.16.33.48
%@isbn 978-85-17-00088-1
%F 59485
%T Detection and validation of forest disturbances using RADARSAT-2 data
%D 2017
%A Staples, Gordon C,
%A Kooij, Marco W van der,
%A Green, Graham R,
%A Chen, Ji K,
%A Gravelle, Shane I,
%A Goodenough, David T,
%@electronicmailaddress gstaples@mda.ca
%E Gherardi, Douglas Francisco Marcolino,
%E Aragão, Luiz Eduardo Oliveira e Cruz de,
%B Simpósio Brasileiro de Sensoriamento Remoto, 18 (SBSR)
%C Santos
%8 28-31 maio 2017
%I Instituto Nacional de Pesquisas Espaciais (INPE)
%J São José dos Campos
%P 7946-7953
%S Anais
%1 Instituto Nacional de Pesquisas Espaciais (INPE)
%X RADARSAT 2 SAR data was used to develop a monitoring program for Canadian forest lands with the aim to provide information on forest harvesting. A study site in British Columbia, Canada, characterized by coniferous forest, was selected. RADARSAT-2 MultiLook Fine mode, acquired from mid-June through mid-September, from 2011 to 2015 was analyzed with the aim to detect forest disturbances. Due to large data volumes and the need for efficiency, an automated end-to-end solution was implemented. The automated solution included image coregistration, temporal filtering, detection of forest disturbances, and delineation of the disturbances. To reduce the detection of false positives, a non-forest mask was developed that entailed a combination of CanVec data that delineated areas such as water bodies, roads, and urban/industrial areas and SAR-derived information such as layover and scattering from urban areas. To assess the performance of the change detection algorithm, the RADARSAT-2 changes were compared to tree-loss information from the Canadian Forest Service (CFS) and cut-block information from the BC Forest Service (BCFS). Since CFS and the BCFS information was representative of annual changes, but the RADARSAT-2 derived changes were representative of summer-only changes, there were discrepancies between the RADARSAT-2 data and the CFS/BCFS data. Notwithstanding these discrepancies, the detection performance was better than 80% for 2011/12 and 2012/13. For 2013/15, however, due to the two-year gap between data acquisition, the detection performance was 74%.
%9 Degradação de florestas
%@language en
%3 59485.pdf